Announcements

Author: Parth Rakesh Desai

Date: Friday, April 1, 2022 at 9:30 AM

Location: Glenn L. Martin Hall, Room EGR-0159

Committee Members:

Professor Siddhartha Das, Chair

Dr. Keir C. Neuman Professor Peter Chung Professor Paul Paukstelis Professor Don DeVoe Professor Jason Kahn, Dean’s Representative

Title of Dissertation: EFFECT OF MISMATCHED BASE PAIRS ON DNA PLECTONEMES 

Abstract: Base pair mismatches in DNA occur during replication and can result in mutations and certain types of cancer.  The exact mechanism by which mismatch repair proteins recognize mismatches is still not well understood. Structures of mismatch recognition proteins bound to a mismatch indicate that the process involves introducing a sharp bend in the DNA and flipping out the mismatched base. Under external torsional stress, an elastic rod with a defect would buckle at the defect, provided the defect reduces the local bending stiffness. In vivo, if the same energetic scenario prevails, it could localize (or pin) the mismatch at the plectoneme end loop (plectoneme refers to a structure formed by the DNA when it buckles and its helical axis wraps or writhes around itself in the presence of a critical torsional stress) and make the mismatched base pair more accessible to the mismatch repair protein. In genomic DNA, however, the entropic cost associated with plectoneme localization could make pinning unfavorable. Magnetic-tweezers-based studies of DNA supercoiling, performed at high salt concentrations, have shown that in DNA harboring a single mismatch, the plectoneme will always localize at the mismatch. Theoretical studies have predicted that under physiological salt concentrations, plectoneme localization becomes probabilistic. However, both experimental and theoretical approaches are currently limited to positively supercoiled DNA. In the current dissertation, we aim to study plectoneme localization, in physiologically relevant conditions, using state-of-the-art molecular dynamics (MD) simulations and single molecule magnetics tweezers-based experiments.

In order to simulate plectoneme localization we first develop a framework using the widely available sequence and salt dependent OxDNA2 model. We verify that the OxDNA2 model can quantitively reproduce a reduction in bending rigidity due to the presence of the mismatch(es), similar to all-atom MD simulations. We then verify that the current framework can reproduce the experimentally observed plectoneme pinning (at the location of the mismatches). Next, we simulate plectoneme pinning under physiologically relevant conditions. We find that the plectoneme pinning (at the location of the mismatches) becomes probabilistic and this probability of plectoneme pinning increases with an increase in the number of mismatches. We also simulate a longer 1010 base pair long DNA to study the influence of entropic effects on plectoneme pinning.

Next, we extend the simulation framework to simulate a negatively supercoiled, i.e., under-wound, DNA molecule.  In vivo, DNA is maintained in a negatively supercoiled state. Negative supercoiling can result in local melting at the mismatched base pairs: this local melting would further reduce the local bending rigidity at the mismatched base pairs and could enhance plectoneme pinning. We find that negative supercoiling significantly enhances plectoneme pinning in comparison with equivalent levels of positive supercoiling. We also find that the mismatched base pairs are locally melted and the plectoneme end loop is bent significantly more as compared to the positive supercoiling case. Additionally, we simulate the 1010 base pair long DNA under two different negative super-helical densities, i.e., two different degrees of unwinding. We find that the super helical density does not affect the plectoneme pinning probabilities. We also conduct simulations of DNA under different stretching forces (0.3 pN, 0.4 pN and 0.6 pN). Negatively supercoiled DNA under relatively high stretching force (~0.6 pN) absorbs tortional stress by locally melting instead of supercoiling. Simulations of DNA under different forces allow us to study the effect of mismatches on the competition between supercoiling and local melting in a negatively supercoiled DNA. We find that higher stretching forces, up to a maximum set by the onset of melting, increase plectoneme pinning at the location of mismatch.

Finally, we propose and develop a single molecule assay to validate the simulations results presented in the previous chapters. Previous single-molecule magnetic tweezers measurements of mismatch DNA buckling and pinning were limited to the high force (~2 pN) – high salt (>0.5 M NaCl) regime. We propose to overcome this limitation by attaching a small gold nano-bead via a di-thiol group close to the mismatched base pairs, which permits direct observation of transient DNA buckling at the mismatch.  We fabricate a DNA substrate that can be used to directly observe plectoneme pinning at the mismatch. We perform single-molecule magnetic tweezers measurements to verify that the presence of the di-thiol group does not result in anomalous pinning in an intact DNA molecule.

Defense Date: Friday April 1, 2022 at 1:00pm

Location: Martin Hall 088-2162

Title: Dynamic Bayesian Network Updating Approaches for Enabling Causal Prognostics and Health Management of Complex Engineering Systems

Committee Members:

Associate Professor Katrina Groth, Chair

Assistant Professor Michelle Bensi

Professor Jeffrey Herrmann

Professor Mohammed Modarres

Professor Gregory Baecher, Dean’s Representative

Abstract:

Complex engineering systems (CESes), such as nuclear power plants or manufacturing plants, are critical to a wide range of industries and utilities; as such, it is important to be able to monitor their system health and make informed decisions on maintenance and risk management practices. However, currently available system-level monitoring approaches either ignore complex dependencies in their probabilistic risk assessments (PRA) or are prognostics and health management (PHM) techniques intended for simpler systems. The gap in CES health management needs to be closed through the development of techniques and models built from a systematic integration of PHM and PRA (SIPPRA) approach that considers a system’s causal factors and operational context when generating health assessments.

The following dissertation describes a concentrated study that addresses one of the challenges facing SIPPRA: how to appropriately discretize a CES’s operational timeline derived from multiple data streams to create discrete time-series data for use as model inputs over meaningful time periods. This research studies how different time scales and discretization approaches impact the performance of dynamic Bayesian Networks (DBNs), models that are increasingly used for causal-based inferences and system-level assessments, specifically built for SIPPRA health management. The impact of this research offers new insight into how to construct such DBNs to better support system-level health management for CESes. 

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https://umd.zoom.us/j/93440317764

Meeting ID: 934 4031 7764

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Author: Md. Turash Haque Pial

Date: Thursday, March 31, 2022 at 3:30 pm

Location: Martin Hall, Room EGR-2162

Committee Members:

Professor Siddhartha Das, Chair

Professor Peter W. Chung

Professor Amir Riaz

Professor Pratyush Tiwary

Professor Yifei Mo, Dean’s Representative

Title of Dissertation: ATOMISTIC EXPLORATION OF DENSELY-GRAFTED POLYELECTROLYTE BRUSHES: EFFECT OF APPLIED ELECTRIC FIELD AND MULTIVALENT SCREENING COUNTERIONS

Abstract: Polyelectrolyte (PE) or charged polymers are ubiquitous under biological and synthetic conditions, ranging from DNA to advanced technologies. PE chains can be grafted on a surface and they extend into solution to form a “brush”-like configuration if the grafting density is high. PE brushes respond to external stimuli by changing their conformation and chemical details, which make them very attractive for numerous applications. Multivalent counterions (neutralizing PE charges) and external electric field are known to significantly affect the brush behavior. Obtaining fundamental insights into PE brush’s response to ions and electric filed is of utmost importance for both industrial and academic research. In this dissertation, we use atomistic tools to improve our understanding of the PE brushes grafted on a single surface and two inner walls of a nanochannel under these two stimuli.

We start by developing an all-atom molecular dynamics simulation framework to test the behavior of the PE brushes (grafted on a single surface) in the presence of externally applied electric fields. It is discovered that the charge density of PE monomers can have significant influence on their response; a smaller monomer charge density helps the brush to tilts along the electric field, while the PE brush with higher monomer charge density bends and shrinks. We found that counterion condensation to PE chains has a substantial impact in controlling these responses.

In the subsequent study we discuss the effect of counterion size and valence in dictating counterion mediated bridging interaction of two or more negative monomers. By examining the solvation behavior, we identify that bridging interactions are not a sole function of the counterion valence. Rather, it depends on the counterion condensation on the PE chain, as well as the size of the counterion solvation shell. We also test the dynamic properties of the counterions and associated bridges.

Later, we proceeded to simulate PE brush-grafted nanochannels to explore equilibrium and flow behavior in presence of nanoconfinement. We identify the onset of overscreening: there are a greater number of coions than counterions in the bulk liquid outside the brush layer. This specific ion distribution ensures that the overall electroosmotic flow is along the direction of the coions. Furthermore, for a large electric field, some of the counterions leave the PE brush layer into the bulk, resulting in disappearance of overscreening. If the number of counterions is greater than coions, electroosmotic flow reverses its direction and follows the motion of counterions. Finally, we discover that counterion-monomer interactions control the ion distribution. As a result, a diverse range of electroosmotic flow is found for counterions with different valence and size.

Author: David Johnson

Date: Friday, March 18, 2022 at 3:30 pm

Location: Martin Hall, Room EGR-0159

List of Committee Members:
Assistant Professor Monifa Vaughn-Cooke, Advisor and Chair
Professor Mohammad Modarres
Professor Jeffrey Herrmann
Assistant Professor Allison Reilly
Professor Gregory Baecher, Dean’s Representative

Title of Paper: ROOT CAUSE ANALYSIS OF ADVERSE EVENTS USING A HUMAN RELIABILITY ANALYSIS APPROACH

Abstract:

Large scale analysis of adverse event data is challenging due to the unstructured nature of event reporting and narrative textual data in adverse event repositories. This issue is further complicated for human error adverse events, which are routinely treated as a root cause instead of as initiating events in a causal chain. Human error events are commonly misunderstood and underreported, which hinders the analysis of trends and the identification of risk mitigation strategies across industries. Currently, the prevailing means of human error investigation is the analysis of accident and incident data which are not designed around a framework of human cognition or psychomotor function. Existing approaches lack a theoretical foundation with sufficient cognitive granularity to identify root causes of human error. This research provides a cognitive task decomposition to standardize the investigation, reporting, and analysis of human error adverse event data in narrative textual form.

The proposed method includes a qualitative structure to answer six questions (when, who, what, where, how, why) that are critical to comprehensively understand the events surrounding human error. This process is accomplished in five main stages: 1) Develop guidelines for a cognitively-driven adverse event investigation; 2) Perform a baseline cognitive task analysis (when) to document relevant stakeholders (who), products or processes (what), and environments (where) based on a taxonomy of cognitive and psychomotor function; 3) Identify deviations for the baseline task analysis in the form of unsafe acts (how) using a human error classification; 4) and Develop a root cause mapping to identify the performance shaping factors (PSFs) (why) for each unsafe act.

The outcome of the proposed method will advance the fields of risk analysis and regulatory science by providing a standardized and repeatable process to input and analyze human error in adverse event databases. The method provides a foundation for more effective human error trending and accident analysis at a greater level of cognitive granularity. Application of this method to adverse event risk mitigations can inform prospective strategies such as resource allocation and system design, with the ultimate long-term goal of reducing the human contribution to risk.